The Data Scientist will analyze complex datasets, develop predictive models, and collaborate with stakeholders to drive data-driven decisions.
Position Summary:
MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems. As part of a global team of developers and analysts, the Data Scientist will work with a larger team to design, build, validate, refine, and operationalize models. This position will sit in Austin, Texas. However, for the right fit, we may consider remote.
Responsibilities:
MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems. As part of a global team of developers and analysts, the Data Scientist will work with a larger team to design, build, validate, refine, and operationalize models. This position will sit in Austin, Texas. However, for the right fit, we may consider remote.
Responsibilities:
- Problem Identification: Collaborate with stakeholders to identify business challenges that can be solved through data analysis.
- Data Collection & Preparation: Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it to ensure accuracy for modeling.
- Model Development: Design and implement algorithms and predictive models using machine learning techniques to forecast outcomes or categorize information.
- Exploratory Data Analysis (EDA): Analyze datasets to uncover hidden patterns, trends, and anomalies.
- Communication & Visualization: Translate technical findings into "data stories" using tools like Tableau or Power BI to influence executive decisions.
- Master’s degree or bachelors degree and equivalent experience in a quantitative field (Math, CS, Stats)
- Programming: Proficiency in Python or R along with SQL for database querying.
- Mathematics & Statistics: Strong foundation in linear algebra, calculus, and statistical modeling.
- Machine Learning: Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
Soft Skills: Critical thinking, curiosity, and the ability to explain complex concepts to non-technical audiences. Experience working with global and remote teams
Similar Jobs
Fintech • Mobile • Payments • Software • Financial Services
Design, develop, and deploy ML models for KYC/KYB, AML, and fraud detection; reduce chargebacks; analyze large datasets for identity and regulatory risk; run A/B tests; build data pipelines and real-time scoring with Python and SQL; collaborate with product, engineering, and compliance to translate requirements into automated solutions.
Top Skills:
GitLarge Language ModelsMachine Learning FrameworksPythonSnowflakeSparkSQL
Artificial Intelligence • Cloud • Security • Software
Partner with Marketing to own attribution, ROI, conversion, and funnel analysis. Design experiments, surface proactive insights, optimize marketing spend, and collaborate with Data/Analytics Engineers to build data models and pipelines. Communicate findings and recommendations to non-technical stakeholders.
Top Skills:
Claude CodeCodexCursorData WarehouseDbtDevinGeminiGithub CopilotPythonSQL
.png)
Logistics • Sales • Software • 3PL: Third Party Logistics
Design, build, evaluate, and deploy NLP and LLM systems (classification, extraction, retrieval). Create evaluation frameworks, golden datasets, and annotation guidelines. Analyze performance, identify failure modes, partner with engineering for production deployment and monitoring, and communicate results to stakeholders.
Top Skills:
Hugging Face TransformersLangchainLangsmithLlmsPythonRagSQL
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
